Habitat fragmentation and logging affect the occurrence of lesser mouse‐deer in tropical forest reserves

Abstract Due to rapid urbanization, logging, and agricultural expansion, forest fragmentation is negatively affecting native wildlife populations throughout the tropics. This study examined the effects of landscape and habitat characteristics on the lesser mouse‐deer, Tragulus kanchil, populations in Peninsular Malaysia. We conducted camera‐trap survey at 315 sampling points located within 8 forest reserves. An assessment of site‐level and landscape variables was conducted at each sampling point. Our study provides critical ecological information for managing and conserving understudied populations of T. kanchil. We found that the detection of T. kanchil was attributed to forest fragmentation in which forest patches had four times greater detection of T. kanchil than continuous forest. The detection of T. kanchil was nearly three times higher in peat swamp forest compared to lowland dipterocarp forests. Surprisingly, the detection of T. kanchil was higher in logged forests (logging ceased at least 30 years ago) than unlogged forests. The detection of T. kanchil increased with the presence of trees, particularly those with DBH of 5 cm to 45 cm, canopy cover, number of saplings and palms, number of dead fallen trees, and distance from nearest roads. However, detection decreased with a greater number of trees with DBH greater than 45 cm and higher elevations, and greater detections where creeping bamboo was abundant. We recommend that conservation stakeholders take the necessary steps (e.g., eradicating poaching, habitat degradation, and further deforestation) to support the conservation of mouse‐deer species and its natural habitats.

Mouse-deer such as T. kanchil plays an important ecological role in forest ecosystems as they are prey for small and large carnivores and are seed dispersers (Feer, 1995;Kawanishi & Sunquist, 2008;Ramesh et al., 2013). Tragulus kanchil consumes high energy food resources such as fallen fruits and also browses vegetation at the understory level, including leaves, tubers, and shoots (Bodmer, 1990;Ramesh et al., 2013). Although T. kanchil is listed as the least-concern species by the International Union for Conservation of Nature (IUCN), little has been published regarding its behavior and ecology in fragmented forest landscapes. In addition, Heydon and Bulloh (1997) showed that selective logging had a negative impact on mouse-deer populations in Sabah. However, it is not yet known whether this would apply in other regions of Southeast Asia.
In this study, we examined the relationship between the occurrence (based on the number of animal detections) of T. kanchil and a range of environmental drivers, including habitat quality, and landscape and forest characteristics using nonintrusive motiontriggered camera traps. The response of T. kanchil to forest fragmentation and habitat modification through logging is poorly understood due to their cryptic behavior. Our study aimed to provide vital information on T. kanchil ecology for forest wildlife management and conservation in the tropics, particularly fragmented forest landscapes.

| Study area
Our study area consisted of eight different forest reserves, which were located in the states of Negeri Sembilan and Selangor in Peninsular Malaysia (  (Karanth & Nichols, 2002). In addition, the repeated theft of camera trap and limited site access in the field constrained sampling periods to 2 weeks or a month. The infrared feature of the Bushnell Trophy Cam consists of a sensor triggered by motion and heat. The camera was set to capture three images per second, with a 1-or 10-s interval between exposures (i.e., taking three photographs per second or 10 s). The interval was set up randomly and varied between cameras throughout the study sites. The cameras were fixed on trees at the height of 30 cm to 50 cm above the ground at angles facing the animal trails. The images captured were sorted down to species level, with species other than T. kanchil excluded from the analysis ( Figure 2). Overexposure and unclear images that led to unidentified F I G U R E 2 Images of Tragulus kanchil captured by camera traps in forest reserves species were also excluded (Sasidhran et al., 2016). Mouse-deer detection in the camera traps was represented by the number of photographic images recorded at each of the 315 sites.

| Assessment of site-level and landscapelevel variables
To  Table 2; Table S1-S3). The selection of variables was based on previous studies (Jamhuri et al., 2018;Sasidhran et al., 2016;Tee et al., 2018) that were conducted to assess the mammal species present in a different type of tropical forest. We also used existing ecological information to guide us in selecting several site-level and landscape variables (e.g., elevation, habitat type, type of forest). For example, some food plants favored by T. kanchil such as Sapium species are found in primary and secondary evergreen to deciduous rain forests, up to 800 m of altitude (Farida et al., 2006).

| Data analysis
We used generalized linear mixed models (GLMMs) to determine the relationship between the occurrence of T. kanchil and the landscape variables. We developed two sets of models to prevent over-fitting during model selection, one set including just site-level variables, and another set including landscape variables. The GLMMs used a Poisson distribution and logarithm link function. We fixed the dispersion parameter for the variance of the response at 1 to adjust for overdispersion. We did not omit the data point with no detections, which we believe could compromise ecological explanations.
Although our data seem to be zero-inflated, that is, the number of zeros is so large that the data do not readily fit standard distributions, this does not necessarily mean a zero-inflated model need to be used. This is because the explanatory variables would predict the zeros under a Poisson model.
We used T. kanchil detection in the camera traps, characterized by the number of photographic images captured at each of the 315 sampling points as a proxy for the occurrence. The occurrence of T. kanchil was used as response variable, which is a function of 12 explanatory variables in the candidate models. To control for correlated structure in the data, the location of the camera trapping point (i.e., forest reserve), year, and time lapse between exposures were included as the random effect. Correlation tests were performed for multicollinearity among the variables in the global models that included landscape variables and in situ covariates. No variable had correlation higher than 0.7 and hence all explanatory variables were included in the analysis (Dormann et al., 2013).
To perform model selection, we fitted all possible regression models and evaluated these according to an Information Theoretic Approach. In this way, a number of best regression models were selected using computer-intensive statistical model building process.
We used Akaike's Information Criterion (AIC) to determine the most parsimonious model based on the minimum values of AIC and calculate the AIC weights (Burnham & Anderson, 2002

| Drivers of T. kanchil occurrence
Out of 13 explanatory variables, 11 variables were strongly correlated with the detection of T. kanchil. The most parsimonious sitelevel model explained 36.74% of the variation in lesser mouse-deer occurrence corresponded to the best subsets with eight terms (  Figure 3). In contrast, the detection of T. kanchil decreased with the number of trees with DBH above 45 cm and elevation. The detection of T. kanchil was not affected by the sampling effort (Table 4; Figure 3).
At landscape level, the most parsimonious model had an adjusted R 2 of 26.64% and included four terms (  (Table 4). The detection of T. kanchil was 2.855 times higher in peat swamp forest compared to lowland dipterocarp landscapes; however, confidence in the coefficient estimate was low and overlapped zero (Table 4). Surprisingly, the detection of T. kanchil was 1.7193 times lower in the unlogged forests compared to the logged forests (Table 4). The distance from nearest roads did not affect the detection of T. kanchil.

| Distribution patterns
The logged forest reserves (BFR, AHFR, BCFR, NSPSF, and SLFR) had higher T. kanchil detection rates compared to the unlogged forest reserves (SMFR, KFR, PFR, and KFR). These results support previous findings, which stated that chevrotains (Tragulus spp.) were relatively more common in the logged forest than in unlogged forest (Granados et al., 2016). A study in Sabah concludes unlogged forest is the preferred habitat by T. kanchil (Heydon & Bulloh, 1997), but this present study found the opposite because of two possible factors. First, the forest reserves we surveyed were selectively logged at least 30 years ago, whereas Heydon and Bulloh (1997) surveyed forests in Sabah that were logged after 2, 5, and 12 years.
Second, they used line-transect surveying, whereas we deployed camera trap, which is more successful at detecting elusive species in tropical forests than line transects (Espartosa et al., 2011;Silveira et al., 2003), and we therefore had more confidence in our result.

| Site-level and landscape-level variable preferences
The detection of T. kanchil across all study sites was highly variable, especially with respect to forest, habitat, and landscape types. Out of eight forest reserves, six were selectively logged at least 30 years ago. This may contribute to the habitat heterogeneity and complexity in the reserves. Tropical forests are heterogeneous and patchy, even without strong anthropogenic disturbances (Whitmore, 1998).
Canopy gaps occur in both undisturbed and disturbed forests as gaps are caused by the death of one or more trees in tropical ecosystems (Kadmon, 2001). Perhaps there were more large gaps in logged forests whereas more small gaps in unlogged forests. Resprouting has been found to be more prevalent underneath small canopy gaps than in large ones (Brown, 2004).
After 30 years or more, through plant succession, tree canopy in logged forests could regenerate and may result in lower light intensity. Our results showed that the T. kanchil detection increased with the percentage of canopy cover. This suggests that T. kanchil prefers habitats of dense evergreen closed-canopy forest. However, the creation of a small canopy gap may increase solar radiation reaching the forest floor and promote the growth of seedlings including those edible to T. kanchil through the enhanced light levels found in the gap (Brown, 2004;Burslem, 2004). Otherwise, only the most shadetolerant plant species can survive and grow in the deep shade of a forest understory (Brown, 2004). In addition, Matsubayashi et al. (2003) found in Borneo that lesser mouse-deer preferred dense undergrowth of creeping bamboo (Dinochloa spp.) with canopy gaps, which is similar to the BCFR and AHFR which included forest areas with lots of bamboo vegetation that resulted in most detection of mouse-deer.
We also found that T. kanchil detection increased with the abundance of trees with a DBH of 5 cm to 45 cm and decreased when tree DBH was greater than 45 cm. These results were supported by previous research, which showed that small ungulates were very active and moved long distances mostly in crown gap areas with dense undergrowth which provide shelter during the day (Matsubayashi et al., 2003). These habitat characteristics are also suitable for foraging as this species predominantly consumes fallen fruits and young leaves from pioneer plants (Bodmer, 1990;. In addition, our results revealed that T. kanchil detections increased with a high number of dead fallen trees. This was similar to a study in Borneo forest that showed T. kanchil rested under shelters such as dead fallen trees or branches. However, it was commonly found foraging in more dense forests (Matsubayashi et al., 2003).
The other covariates also support T. kanchil's preference for areas that are associated with forest gaps. For example, the detection of T. kanchil increased in areas with a high number of saplings. Tragulus kanchil possibly relies on food resources close to the dense forest floor in open canopy areas such as short vegetation and fallen fruits (Jayasekara et al., 2007;Matsubayashi et al., 2003). Areas with understory cover and high leaf litter are suitable for T. kanchil to forage for food and provide refuge for small-bodied ungulates.

| Impact of human disturbances
Our results indicated that the occurrence of T. kanchil was greater in patches than continuous forests. This finding showed that T. kanchil populations could persist in forest patches. This particular finding can be explained by the absence of natural predators in the forest patches (Khalidah et al., 2021;Tee et al., 2018). Tragulus kanchil was probably preyed on by leopards, feral dogs, and pythons in the forest reserves. In addition, T. kanchil might thrive in forest patches because of the lack of competition and high resource availability (e.g., fruits of pioneer species).
Tragulus kanchil was also positively impacted by human disturbance. The mouse-deer was more likely to inhabit the logged forest compared to unlogged forest. This is because the logged forest may provide more plant food resources in their understory. Unlike larger grazing and browsing species, T. kanchil tends to be a selective feeder and it does not need to gather large quantities of food daily (Heydon & Bulloh, 1997). Tragulus kanchil spends more time selecting more edible leaves, shoots, flowers, and fruits (Matsubayashi & Sukor, 2005). In contrast, Magintan et al. (2017) (Ickes & Thomas, 2003).
The mouse-deer populations have been threatened by extensive land clearing and poaching across their known habitat (Azhar et al., 2013;Petersen et al., 2020). Nguyen et al. (2019) suggest that snares laid by hunters have pushed the species to the brink of extinction in Vietnam. However, we did not encounter any traps in our study area.
Poaching is believed to occur year-round although hunting is prohibited within the forest reserves (Goldthorpe & Neo, 2011).

| CON CLUS ION
The results from this study provide valuable information to stakeholders supporting the conservation of existing forest patches irrespective of size. To conserve the habitat of T. kanchil in the forest reserves, they should monitor and manage site-level habitat quality.
The occurrence of T. kanchil was influenced by forest fragmentation.
However, both forest patch and continuous forest are equally crucial for conserving T. kanchil populations. Our data give a preliminary indication that T. kanchil may prefer peat swamps forests, which justifies the conservation of peat swamp forests as one of the critical habitats in Southeast Asia. This study also showed that logged forest had a higher detection of T. kanchil compared to the unlogged forest. This suggests that logged forest should not be sidelined because of its conservation value for T. kanchil. We suggest more research into the anthropogenic threats in elsewhere across Southeast Asia where T. kanchil lives to protect them better. Tragulus kanchil has a good chance of survival in forestry landscapes if the key threats are removed.

ACK N OWLED G M ENTS
We thank the staff from the Forestry Department of Selangor and Negeri Sembilan for their cooperation. We are grateful to Muhammad Ashraf and Tharani Alapagan for assisting us in the field.

CO N FLI C T O F I NTE R E S T
The authors declare that they have no conflict of interest.